Overview

Dataset statistics

Number of variables9
Number of observations43
Missing cells2
Missing cells (%)0.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory81.1 B

Variable types

Categorical4
Numeric5

Dataset

Description지방세비과감면율현황( 시도명, 시군구명, 자치단체코드, 세목명, 과세연도, 비과세금액, 감면금액, 부과금액, 비가세감면율 등) 정보 공개
Author경기도 동두천시
URLhttps://www.data.go.kr/data/15079285/fileData.do

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
자치단체코드 has constant value ""Constant
비과세금액 is highly overall correlated with 감면금액 and 2 other fieldsHigh correlation
감면금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
부과금액 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세감면율 is highly overall correlated with 비과세금액 and 2 other fieldsHigh correlation
비과세금액 has 2 (4.7%) missing valuesMissing
감면금액 has unique valuesUnique
비과세금액 has 5 (11.6%) zerosZeros
부과금액 has 5 (11.6%) zerosZeros
비과세감면율 has 6 (14.0%) zerosZeros

Reproduction

Analysis started2023-12-12 08:19:21.568085
Analysis finished2023-12-12 08:19:25.400882
Duration3.83 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
경기도
43 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기도
2nd row경기도
3rd row경기도
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 43
100.0%

Length

2023-12-12T17:19:25.459320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:19:25.553622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 43
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
동두천시
43 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row동두천시
2nd row동두천시
3rd row동두천시
4th row동두천시
5th row동두천시

Common Values

ValueCountFrequency (%)
동두천시 43
100.0%

Length

2023-12-12T17:19:25.676504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:19:25.806404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
동두천시 43
100.0%

자치단체코드
Categorical

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size476.0 B
41250
43 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row41250
2nd row41250
3rd row41250
4th row41250
5th row41250

Common Values

ValueCountFrequency (%)
41250 43
100.0%

Length

2023-12-12T17:19:25.934197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:19:26.072533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
41250 43
100.0%

세목명
Categorical

Distinct8
Distinct (%)18.6%
Missing0
Missing (%)0.0%
Memory size476.0 B
등록세
6 
재산세
6 
주민세
6 
취득세
6 
자동차세
6 
Other values (3)
13 

Length

Max length7
Median length3
Mean length3.9767442
Min length3

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row등록세
2nd row재산세
3rd row주민세
4th row취득세
5th row자동차세

Common Values

ValueCountFrequency (%)
등록세 6
14.0%
재산세 6
14.0%
주민세 6
14.0%
취득세 6
14.0%
자동차세 6
14.0%
등록면허세 6
14.0%
지역자원시설세 6
14.0%
교육세 1
 
2.3%

Length

2023-12-12T17:19:26.201126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:19:26.367876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
등록세 6
14.0%
재산세 6
14.0%
주민세 6
14.0%
취득세 6
14.0%
자동차세 6
14.0%
등록면허세 6
14.0%
지역자원시설세 6
14.0%
교육세 1
 
2.3%

과세연도
Real number (ℝ)

Distinct6
Distinct (%)14.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2019.5581
Minimum2017
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T17:19:26.535844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2017
5-th percentile2017
Q12018
median2020
Q32021
95-th percentile2022
Maximum2022
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7498616
Coefficient of variation (CV)0.00086645763
Kurtosis-1.3030462
Mean2019.5581
Median Absolute Deviation (MAD)2
Skewness-0.031758345
Sum86841
Variance3.0620155
MonotonicityIncreasing
2023-12-12T17:19:26.681389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
2022 8
18.6%
2017 7
16.3%
2018 7
16.3%
2019 7
16.3%
2020 7
16.3%
2021 7
16.3%
ValueCountFrequency (%)
2017 7
16.3%
2018 7
16.3%
2019 7
16.3%
2020 7
16.3%
2021 7
16.3%
2022 8
18.6%
ValueCountFrequency (%)
2022 8
18.6%
2021 7
16.3%
2020 7
16.3%
2019 7
16.3%
2018 7
16.3%
2017 7
16.3%

비과세금액
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct37
Distinct (%)90.2%
Missing2
Missing (%)4.7%
Infinite0
Infinite (%)0.0%
Mean1.1916708 × 109
Minimum0
Maximum8.168053 × 109
Zeros5
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T17:19:26.830157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12245000
median1.33694 × 108
Q37.21251 × 108
95-th percentile6.708188 × 109
Maximum8.168053 × 109
Range8.168053 × 109
Interquartile range (IQR)7.19006 × 108

Descriptive statistics

Standard deviation2.3443301 × 109
Coefficient of variation (CV)1.9672631
Kurtosis3.0717225
Mean1.1916708 × 109
Median Absolute Deviation (MAD)1.33121 × 108
Skewness2.1043562
Sum4.8858504 × 1010
Variance5.4958835 × 1018
MonotonicityNot monotonic
2023-12-12T17:19:26.988385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 5
 
11.6%
74539000 1
 
2.3%
2023558000 1
 
2.3%
153265000 1
 
2.3%
751000 1
 
2.3%
133694000 1
 
2.3%
7809062000 1
 
2.3%
41196000 1
 
2.3%
1219977000 1
 
2.3%
160865000 1
 
2.3%
Other values (27) 27
62.8%
(Missing) 2
 
4.7%
ValueCountFrequency (%)
0 5
11.6%
250000 1
 
2.3%
573000 1
 
2.3%
661000 1
 
2.3%
751000 1
 
2.3%
1475000 1
 
2.3%
2245000 1
 
2.3%
3097000 1
 
2.3%
41196000 1
 
2.3%
41443000 1
 
2.3%
ValueCountFrequency (%)
8168053000 1
2.3%
7809062000 1
2.3%
6708188000 1
2.3%
6487126000 1
2.3%
5601912000 1
2.3%
4620597000 1
2.3%
2023558000 1
2.3%
1692826000 1
2.3%
1219977000 1
2.3%
977287000 1
2.3%

감면금액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4878967 × 108
Minimum6000
Maximum3.860807 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T17:19:27.135917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6000
5-th percentile2456200
Q141987000
median98113000
Q31.1649575 × 109
95-th percentile2.6695194 × 109
Maximum3.860807 × 109
Range3.860801 × 109
Interquartile range (IQR)1.1229705 × 109

Descriptive statistics

Standard deviation9.659025 × 108
Coefficient of variation (CV)1.488776
Kurtosis2.2985681
Mean6.4878967 × 108
Median Absolute Deviation (MAD)95728000
Skewness1.7361983
Sum2.7897956 × 1010
Variance9.3296765 × 1017
MonotonicityNot monotonic
2023-12-12T17:19:27.307578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
2385000 1
 
2.3%
1157093000 1
 
2.3%
2694314000 1
 
2.3%
434273000 1
 
2.3%
38507000 1
 
2.3%
82123000 1
 
2.3%
4781000 1
 
2.3%
1279975000 1
 
2.3%
98113000 1
 
2.3%
3860807000 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
6000 1
2.3%
415000 1
2.3%
2385000 1
2.3%
3097000 1
2.3%
4081000 1
2.3%
4781000 1
2.3%
9509000 1
2.3%
32348000 1
2.3%
36247000 1
2.3%
38507000 1
2.3%
ValueCountFrequency (%)
3860807000 1
2.3%
2830753000 1
2.3%
2694314000 1
2.3%
2446368000 1
2.3%
2322008000 1
2.3%
2214639000 1
2.3%
1468750000 1
2.3%
1281114000 1
2.3%
1279975000 1
2.3%
1239598000 1
2.3%

부과금액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)90.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.3991431 × 109
Minimum0
Maximum3.8717331 × 1010
Zeros5
Zeros (%)11.6%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T17:19:27.489129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11.738377 × 109
median3.767639 × 109
Q31.3918094 × 1010
95-th percentile2.4651451 × 1010
Maximum3.8717331 × 1010
Range3.8717331 × 1010
Interquartile range (IQR)1.2179718 × 1010

Descriptive statistics

Standard deviation8.9574343 × 109
Coefficient of variation (CV)1.06647
Kurtosis1.8552596
Mean8.3991431 × 109
Median Absolute Deviation (MAD)3.767639 × 109
Skewness1.3689441
Sum3.6116316 × 1011
Variance8.0235629 × 1019
MonotonicityNot monotonic
2023-12-12T17:19:27.652999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
0 5
 
11.6%
13797799000 1
 
2.3%
24886975000 1
 
2.3%
9335481000 1
 
2.3%
2099480000 1
 
2.3%
3265384000 1
 
2.3%
14750353000 1
 
2.3%
1753432000 1
 
2.3%
38717331000 1
 
2.3%
12239287000 1
 
2.3%
Other values (29) 29
67.4%
ValueCountFrequency (%)
0 5
11.6%
18112000 1
 
2.3%
1485410000 1
 
2.3%
1613533000 1
 
2.3%
1713282000 1
 
2.3%
1714806000 1
 
2.3%
1730495000 1
 
2.3%
1746259000 1
 
2.3%
1753432000 1
 
2.3%
1937832000 1
 
2.3%
ValueCountFrequency (%)
38717331000 1
2.3%
27307070000 1
2.3%
24886975000 1
2.3%
22531735000 1
2.3%
20749442000 1
2.3%
19854733000 1
2.3%
15752553000 1
2.3%
14750353000 1
2.3%
14336328000 1
2.3%
14332784000 1
2.3%

비과세감면율
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)72.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.38907
Minimum0
Maximum61.62
Zeros6
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-12T17:19:27.824389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q13.435
median6.29
Q314.475
95-th percentile55.9
Maximum61.62
Range61.62
Interquartile range (IQR)11.04

Descriptive statistics

Standard deviation18.518912
Coefficient of variation (CV)1.2870124
Kurtosis1.3270855
Mean14.38907
Median Absolute Deviation (MAD)4.48
Skewness1.6447236
Sum618.73
Variance342.9501
MonotonicityNot monotonic
2023-12-12T17:19:27.976818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0.0 6
 
14.0%
6.0 5
 
11.6%
5.0 2
 
4.7%
2.0 2
 
4.7%
9.0 2
 
4.7%
5.25 1
 
2.3%
1.81 1
 
2.3%
5.37 1
 
2.3%
13.95 1
 
2.3%
6.61 1
 
2.3%
Other values (21) 21
48.8%
ValueCountFrequency (%)
0.0 6
14.0%
1.2 1
 
2.3%
1.81 1
 
2.3%
1.87 1
 
2.3%
2.0 2
 
4.7%
4.87 1
 
2.3%
5.0 2
 
4.7%
5.25 1
 
2.3%
5.37 1
 
2.3%
6.0 5
11.6%
ValueCountFrequency (%)
61.62 1
2.3%
59.98 1
2.3%
56.0 1
2.3%
55.0 1
2.3%
52.5 1
2.3%
48.0 1
2.3%
42.49 1
2.3%
23.87 1
2.3%
21.0 1
2.3%
17.63 1
2.3%

Interactions

2023-12-12T17:19:24.582558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:21.848614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:22.458111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.355008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.008143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.675981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:21.965188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:22.569706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.506443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.115289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.780836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:22.071090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.005045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.653210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.228932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.899822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:22.202605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.119937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.779735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.359901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:25.043509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:22.332028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.228055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:23.888346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:19:24.473797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:19:28.100430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
세목명과세연도비과세금액감면금액부과금액비과세감면율
세목명1.0000.0000.6570.7580.7540.874
과세연도0.0001.0000.0000.0000.0000.000
비과세금액0.6570.0001.0000.9500.7500.969
감면금액0.7580.0000.9501.0000.8890.874
부과금액0.7540.0000.7500.8891.0000.564
비과세감면율0.8740.0000.9690.8740.5641.000
2023-12-12T17:19:28.287624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
과세연도비과세금액감면금액부과금액비과세감면율세목명
과세연도1.0000.034-0.0340.061-0.0700.000
비과세금액0.0341.0000.8850.8780.6900.263
감면금액-0.0340.8851.0000.8680.7380.468
부과금액0.0610.8780.8681.0000.5530.488
비과세감면율-0.0700.6900.7380.5531.0000.475
세목명0.0000.2630.4680.4880.4751.000

Missing values

2023-12-12T17:19:25.195445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:19:25.345891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

시도명시군구명자치단체코드세목명과세연도비과세금액감면금액부과금액비과세감면율
0경기도동두천시41250등록세20170238500000.0
1경기도동두천시41250재산세2017648712600011570930001379779900055.0
2경기도동두천시41250주민세2017745390006674300016135330009.0
3경기도동두천시41250취득세2017202355800023220080002074944200021.0
4경기도동두천시41250자동차세2017300794000313136000107249470006.0
5경기도동두천시41250등록면허세201730970009062000017462590005.0
6경기도동두천시41250지역자원시설세201711572000010973000038597030006.0
7경기도동두천시41250등록세20180408100000.0
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9경기도동두천시41250주민세2018744690006625700017148060008.0
시도명시군구명자치단체코드세목명과세연도비과세금액감면금액부과금액비과세감면율
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42경기도동두천시41250지역자원시설세20221529250008291700044937230005.25